Argos

Driving purchase frequency for Argos’ digital team.

- BUSINESS GOAL -

As part of the strategic objective of "More Argos, More Often," we collaborated with the digital team to identify propositions that could increase purchase frequency and spend among existing Argos shoppers.

The goal was to introduce a new mechanic or proposition that would disrupt current purchasing habits, capturing spend from key competitors in specific product categories. The team had a range of new mechanics they wanted to test, including ideas related to discounts, fulfillment, and loyalty rewards. To ensure the success of these propositions, research was needed to compare and stress-test these ideas among infrequent Argos customers while ensuring that the winning concepts appealed to three target segments.

With a 5-week timeframe, we knew that our approach needed to be agile while still being robust enough to provide confidence in our findings.

- THE SOLUTION -

We adopted a blended approach, beginning with a qualitative phase to understand the existing brand perceptions of Argos and identify barriers to shopping. This phase also allowed us to explore reactions to different mechanics and determine which were most likely to change behavior – and why.

We followed this with a quantitative phase, using techniques like max diff, TURF, and key drivers analysis to compare 20 different mechanics. This rigorous analysis provided the digital team with a clear prioritization framework for their strategic decision-making.

When reporting our findings, we applied the EAST behavioral science framework to assess each mechanism based on its ease, attractiveness, social impact, and timeliness. This helped contextualize our results and strengthen our recommendations. Additionally, we integrated the framework into both the discussion guide and the questionnaire, helping us identify why the most successful mechanics were likely to influence Argos’ purchase frequency.

- THE OUTCOME -

Max diff allowed us to go beyond a simple robust sample size and assess each mechanic from multiple perspectives. As a result, we were able to confidently recommend which mechanics Argos should prioritize, based on their appeal among target consumers.

We also identified a set of six KPIs to benchmark each mechanic, looking at elements beyond appeal—such as ease of use and relevance.

Using TURF (Total Unduplicated Reach and Frequency) analysis, we demonstrated which combinations of mechanics would maximize reach among the target audience and identified any disparities between the different target segments.

If you’re interested in learning more about this project or how running a drivers analysis for your own product, reach out to Nathan to book in a call or get a copy of our creds deck.